Generative AI Engineer
Role details
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Tech stack
Job description
This position is an addition to the Pro Code & AI team to support the extended responsibilities of scaling AI-driven solutions within the Digital Finance function. As an Generative AI Engineer (m/f/d), this role is critical for advancing our capabilities beyond pilots and prototypes to sustainably strengthen digitalization with production-grade AI. To achieve this, the role is structured around three core areas: architecting and developing advanced Generative AI solutions, engineering scalable MLOps and API deployment pipelines, and providing expert-level system evaluation and strategic guidance. This focus ensures the transition from experimental models to robust, integrated business applications. Given the emphasis on productionizing AI, the ideal candidate will be a recognized master in the field, possessing extensive experience in Python, GenAI frameworks like LangChain, RAG architecture, and API development. They will be responsible for establishing operational plans and implementing new processes that have a significant impact on achieving our functional results., * Design and deliver production-grade Generative AI agents and workflows using foundation models with frameworks such as LangChain and LangGraph.
- Architect, build, and optimize scalable Retrieval-Augmented Generation (RAG) systems using vector stores like FAISS or Redis.
- Integrate structured enterprise data (e.g., Snowflake) with unstructured sources (PDFs, documents, text corpora) into unified AI solutions.
- Fine-tune or adapt language models using LoRA/PEFT techniques to meet domain-specific and business requirements.
- Develop and deploy secure, containerized Generative AI APIs using FastAPI or Flask, with Docker-based deployments.
- Implement MLOps and CI/CD pipelines for automated testing, deployment, monitoring, and lifecycle management of AI systems.
- Define and apply evaluation frameworks (RAGAS, LangSmith) to measure quality, reliability, and continuous performance improvement.
- Provide strategic leadership through best-practice definition, ethical AI governance, technical documentation, and team mentorship.
Requirements
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related quantitative discipline.
- Extensive professional experience as a senior expert in software engineering and applied machine learning, aligned with a P5 Expert Professional level.
- Proven track record designing, building, and deploying production-scale AI/ML systems, with deep focus on Generative AI solutions.
- Strong expertise in Generative AI, Large Language Models, and modern frameworks such as LangChain and LangGraph.
- Advanced software and systems engineering skills with strong Python proficiency and API design experience.
- Hands-on experience deploying AI systems on cloud platforms such as AWS and Microsoft Azure.
- Demonstrated analytical thinking and troubleshooting skills for complex technical and business problems.
- Recognized thought leader with the ability to influence, mentor, and communicate complex concepts effectively.